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» A Study of Empirical Learning for an Involved Problem
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ML
2010
ACM
193views Machine Learning» more  ML 2010»
14 years 6 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
ECSQARU
2009
Springer
15 years 6 months ago
Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks
To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...
CP
2006
Springer
15 years 3 months ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
JMLR
2010
145views more  JMLR 2010»
14 years 6 months ago
Kernel Partial Least Squares is Universally Consistent
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
Gilles Blanchard, Nicole Krämer
TCC
2005
Springer
102views Cryptology» more  TCC 2005»
15 years 5 months ago
Toward Privacy in Public Databases
Abstract. We initiate a theoretical study of the census problem. Informally, in a census individual respondents give private information to a trusted party (the census bureau), who...
Shuchi Chawla, Cynthia Dwork, Frank McSherry, Adam...